The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.
Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists
Open accessAbstract
Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).
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Citations
Cites
Object based image analysis for remote sensing
Blaschke, T. (2010) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2009.06.004 · Cited by 4,482
A survey of image classification methods and techniques for improving classification performance
Lu, D., & Weng, Q. (2007) · International Journal of Remote Sensing · doi:10.1080/01431160600746456 · Cited by 3,402
Haboudane, D. (2004) · Remote Sensing of Environment · doi:10.1016/j.rse.2003.12.013 · Cited by 2,608
Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information
Benz, U. C., Hofmann, P., Willhauck, G., Lingenfelder, I., & Heynen, M. (2004) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2003.10.002 · Cited by 2,530
Remote Sensing of the Environment: An Earth Resource Perspective
Jensen, J. R. (2000) · Cited by 2,448
Review article Multisensor image fusion in remote sensing: Concepts, methods and applications
Pohl, C., & Van Genderen, J. L. (1998) · International Journal of Remote Sensing · doi:10.1080/014311698215748 · Cited by 2,211
An assessment of support vector machines for land cover classification
Huang, C., Davis, L. S., & Townshend, J. R. G. (2002) · International Journal of Remote Sensing · doi:10.1080/01431160110040323 · Cited by 1,795
Geographic Object-Based Image Analysis – Towards a new paradigm
Blaschke, T., Hay, G. J., Kelly, M., Lang, S., Hofmann, P., Addink, E., Queiroz Feitosa, R., van der Meer, F., van der Werff, H., van Coillie, F., et al. (2014) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2013.09.014 · Cited by 1,647
Airborne laser scanning—an introduction and overview
Wehr, A., & Lohr, U. (1999) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(99)00011-8 · Cited by 1,414
Remote sensing for biodiversity science and conservation
Turner, W., Spector, S., Gardiner, N., Fladeland, M., Sterling, E., & Steininger, M. (2003) · Trends in Ecology & Evolution · doi:10.1016/s0169-5347(03)00070-3 · Cited by 1,404
Cited by
Ball, J. E., Anderson, D. T., & Chan, C. S. (2017) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.11.042609 · Cited by 746
Metadata
- Authors
- Wang, K., Franklin, S. E., Guo, X., & Cattet, M.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2010-11-01
- Volume
- 10
- Issue
- 11
- Pages
- 9647-9667
- ISSN
- 1424-8220 (ISSN-L)
- OpenAlex
- W2028956118
- Cited by
- 320
- References
- 67
- FWCI
- 9.52
- Type
- journal article
- Language
- en
- Open access
- gold
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- Wang, K., Franklin, S. E., Guo, X., & Cattet, M. (2010). Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists. Sensors. https://doi.org/10.3390/s101109647
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
